Using crowdsourced data to analyze transport crime

Figures & data

Table 1. Average hourly labour costs in € in Europe for selected countries (Eurostat 2017).

Total average hourly labour costs (in €)	2016
Sweden (EU15)	39.9
Denmark (EU15)	39.1
Netherlands (EU15)	33.7
Germany (EU15)	27.1
CZ (EU12)	9.4
Poland (EU12)	7.6
Romania (EU12)	4.3
Bulgaria (EU12)	3.6

Note: The category ‘Construction’ was used, as this is the work category closest to truck driving in terms of conditions (the other categories in Eurostat are Business Economy, Industry and Services). Detailed working conditions of EU12 truck drivers can be found in COWI (2015).

Figure 1. The app, named after the study (Cabotagestudien, available at the App Store and Google Play). Volunteers download the app, register licence plate numbers and add comments on nationality, for example.

Figure 2. The left image shows the movement pattern of a truck, based on volunteer observations. The right image shows the actual movement pattern of the same truck, based on the GPS of the fleet management system of the haulier (Sternberg et al. 2015).

Table 2. Descriptive statistics.

	Mean	SD	Skewness	Kurtosis
Population	33,611.6	69,275.2	8.9	99.8
x9821 (Diesel thefts)	5.8	7.7	3.2	14.6
x9803 (Theft of trucks and trailers)	0.4	1.3	7.7	75.1
x9804 (Theft from trucks and trailers)	1.4	4.3	8.3	88.9
CS_LOW	137.8	670.4	7.8	70.2
CS_HIGH	660.0	4060.2	12.1	167.3

Table 3. Hierarchical regression – thefts of trucks or trailers.

Model	F	p-Value	R^2	Variable	B	Std. error	p-Value
1	206	<.001	0.417	(Constant)	−0.316	0.049	<.001
				S_POP	0.004	<0.001	<.001
2	95.2	<.001	0.500	(Constant)	−0.142	0.052	.007
				POP	0.002	<0.001	<.001
				CS_LOW	0.006	0.007	.400
				CS_ HIGH	0.008	0.003	.013

Table 4. Hierarchical regression – thefts from trucks or trailers.

Model	F	p-Value	R^2	Variable	B	Std. error	p-Value
1	293	<.001	0.504	(Constant)	−0.495	0.078	<.001
				S_POP	0.007	<0.001	<.001
2	137	<.001	0.589	(Constant)	−0.213	0.082	.010
				POP	0.004	0.001	<.001
				CS_LOW	0.028	0.010	.006
				CS_ HIGH	0.005	0.005	.326

Table 5. Hierarchical regression – diesel thefts.

Model	F	p-Value	R^2	Variable	B	Std. error	p-Value
1	248	<.001	0.463	(Constant)	0.446	0.114	<.001
				S_POP	0.010	0.001	<.001
2	100	<.001	0.512	(Constant)	0.728	0.125	<.001
				POP	0.007	0.001	<.001
				CS_LOW	0.041	0.016	.010
				CS_ HIGH	−0.001	0.008	.974

Table 6. Correlation coefficients.

	POP	CS_LOW
CS_LOW	0.696
CS_ HIGH	0.746	0.940

Eurostat. 2017. “Hourly Labour Costs.”. http://ec.europa.eu/eurostat/statistics-explained/index.php/Hourly_labour_costs. Accessed 5 January 2018.

 Google Scholar

COWI. 2015. Sidveje i Dansk Transport. Copenhagen: DTL.

 Google Scholar

Sternberg, Henrik, Michal Filipiak, Erik Hofmann, and Daniel Hellström. 2015. Cabotagestudien: A Study on Trucking Deregulation in Scandinavia and Beyond. Lund: Lund University.

 Google Scholar